{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 线性回归预测房价"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**任务:**\n",
    "基于usa_housing_price.csv数据，建立线性回归模型，预测合理房价：\n",
    "1、以面积为输入变量，建立单因子模型，评估模型表现，可视化线性回归预测结果\n",
    "2、以income、house age、numbers of rooms、population、area为输入变量，建立多因子模型，评估模型表现\n",
    "3、预测Income=65000, House Age=5, Number of Rooms=5, Population=30000,size=200的合理房价\n",
    "X_test = [65000,5,5,30000,200]"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "@Author  : Flare Zhao\n",
    "@Email: 454209979@qq.com\n",
    "@QQ讨论群：530533630  申请加群的验证信息为订单号（粘贴号码数字即可）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Avg. Area Income</th>\n",
       "      <th>Avg. Area House Age</th>\n",
       "      <th>Avg. Area Number of Rooms</th>\n",
       "      <th>Area Population</th>\n",
       "      <th>size</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>79545.45857</td>\n",
       "      <td>5.317139</td>\n",
       "      <td>7.009188</td>\n",
       "      <td>23086.80050</td>\n",
       "      <td>188.214212</td>\n",
       "      <td>1.059034e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>79248.64245</td>\n",
       "      <td>4.997100</td>\n",
       "      <td>6.730821</td>\n",
       "      <td>40173.07217</td>\n",
       "      <td>160.042526</td>\n",
       "      <td>1.505891e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>61287.06718</td>\n",
       "      <td>5.134110</td>\n",
       "      <td>8.512727</td>\n",
       "      <td>36882.15940</td>\n",
       "      <td>227.273544</td>\n",
       "      <td>1.058988e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>63345.24005</td>\n",
       "      <td>3.811764</td>\n",
       "      <td>5.586729</td>\n",
       "      <td>34310.24283</td>\n",
       "      <td>164.816630</td>\n",
       "      <td>1.260617e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>59982.19723</td>\n",
       "      <td>5.959445</td>\n",
       "      <td>7.839388</td>\n",
       "      <td>26354.10947</td>\n",
       "      <td>161.966659</td>\n",
       "      <td>6.309435e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Avg. Area Income  Avg. Area House Age  Avg. Area Number of Rooms  \\\n",
       "0       79545.45857             5.317139                   7.009188   \n",
       "1       79248.64245             4.997100                   6.730821   \n",
       "2       61287.06718             5.134110                   8.512727   \n",
       "3       63345.24005             3.811764                   5.586729   \n",
       "4       59982.19723             5.959445                   7.839388   \n",
       "\n",
       "   Area Population        size         Price  \n",
       "0      23086.80050  188.214212  1.059034e+06  \n",
       "1      40173.07217  160.042526  1.505891e+06  \n",
       "2      36882.15940  227.273544  1.058988e+06  \n",
       "3      34310.24283  164.816630  1.260617e+06  \n",
       "4      26354.10947  161.966659  6.309435e+05  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#load the data\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "data = pd.read_csv('usa_housing_price.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib import pyplot as plt\n",
    "fig = plt.figure(figsize=(10,10))\n",
    "fig1 =plt.subplot(231)\n",
    "plt.scatter(data.loc[:,'Avg. Area Income'],data.loc[:,'Price'])\n",
    "plt.title('Price VS Income')\n",
    "\n",
    "fig2 =plt.subplot(232)\n",
    "plt.scatter(data.loc[:,'Avg. Area House Age'],data.loc[:,'Price'])\n",
    "plt.title('Price VS House Age')\n",
    "\n",
    "fig3 =plt.subplot(233)\n",
    "plt.scatter(data.loc[:,'Avg. Area Number of Rooms'],data.loc[:,'Price'])\n",
    "plt.title('Price VS Number of Rooms')\n",
    "\n",
    "fig4 =plt.subplot(234)\n",
    "plt.scatter(data.loc[:,'Area Population'],data.loc[:,'Price'])\n",
    "plt.title('Price VS Area Population')\n",
    "\n",
    "fig5 =plt.subplot(235)\n",
    "plt.scatter(data.loc[:,'size'],data.loc[:,'Price'])\n",
    "plt.title('Price VS size')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.059034e+06\n",
       "1    1.505891e+06\n",
       "2    1.058988e+06\n",
       "3    1.260617e+06\n",
       "4    6.309435e+05\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#define X and y\n",
    "X = data.loc[:,'size']\n",
    "y = data.loc[:,'Price']\n",
    "y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5000, 1)\n"
     ]
    }
   ],
   "source": [
    "X = np.array(X).reshape(-1,1)\n",
    "print(X.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#set up the linear regression model\n",
    "from sklearn.linear_model import LinearRegression\n",
    "LR1 = LinearRegression()\n",
    "#train the model\n",
    "LR1.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1276881.85636623 1173363.58767144 1420407.32457443 ... 1097848.86467426\n",
      " 1264502.88144558 1131278.58816273]\n"
     ]
    }
   ],
   "source": [
    "#calculate the price vs size\n",
    "y_predict_1 = LR1.predict(X)\n",
    "print(y_predict_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "108771672553.6264 0.1275031240418234\n"
     ]
    }
   ],
   "source": [
    "#evaluate the model\n",
    "from sklearn.metrics import mean_squared_error,r2_score\n",
    "mean_squared_error_1 = mean_squared_error(y,y_predict_1)\n",
    "r2_score_1 = r2_score(y,y_predict_1)\n",
    "print(mean_squared_error_1,r2_score_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig6 = plt.figure(figsize=(8,5))\n",
    "plt.scatter(X,y)\n",
    "plt.plot(X,y_predict_1,'r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Avg. Area Income</th>\n",
       "      <th>Avg. Area House Age</th>\n",
       "      <th>Avg. Area Number of Rooms</th>\n",
       "      <th>Area Population</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>79545.45857</td>\n",
       "      <td>5.317139</td>\n",
       "      <td>7.009188</td>\n",
       "      <td>23086.80050</td>\n",
       "      <td>188.214212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>79248.64245</td>\n",
       "      <td>4.997100</td>\n",
       "      <td>6.730821</td>\n",
       "      <td>40173.07217</td>\n",
       "      <td>160.042526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>61287.06718</td>\n",
       "      <td>5.134110</td>\n",
       "      <td>8.512727</td>\n",
       "      <td>36882.15940</td>\n",
       "      <td>227.273544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>63345.24005</td>\n",
       "      <td>3.811764</td>\n",
       "      <td>5.586729</td>\n",
       "      <td>34310.24283</td>\n",
       "      <td>164.816630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>59982.19723</td>\n",
       "      <td>5.959445</td>\n",
       "      <td>7.839388</td>\n",
       "      <td>26354.10947</td>\n",
       "      <td>161.966659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>60567.94414</td>\n",
       "      <td>3.169638</td>\n",
       "      <td>6.137356</td>\n",
       "      <td>22837.36103</td>\n",
       "      <td>161.641403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>78491.27543</td>\n",
       "      <td>4.000865</td>\n",
       "      <td>6.576763</td>\n",
       "      <td>25616.11549</td>\n",
       "      <td>159.164596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>63390.68689</td>\n",
       "      <td>3.749409</td>\n",
       "      <td>4.805081</td>\n",
       "      <td>33266.14549</td>\n",
       "      <td>139.491785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>68001.33124</td>\n",
       "      <td>5.465612</td>\n",
       "      <td>7.130144</td>\n",
       "      <td>42625.62016</td>\n",
       "      <td>184.845371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>65510.58180</td>\n",
       "      <td>5.007695</td>\n",
       "      <td>6.792336</td>\n",
       "      <td>46501.28380</td>\n",
       "      <td>148.589423</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Avg. Area Income  Avg. Area House Age  Avg. Area Number of Rooms  \\\n",
       "0          79545.45857             5.317139                   7.009188   \n",
       "1          79248.64245             4.997100                   6.730821   \n",
       "2          61287.06718             5.134110                   8.512727   \n",
       "3          63345.24005             3.811764                   5.586729   \n",
       "4          59982.19723             5.959445                   7.839388   \n",
       "...                ...                  ...                        ...   \n",
       "4995       60567.94414             3.169638                   6.137356   \n",
       "4996       78491.27543             4.000865                   6.576763   \n",
       "4997       63390.68689             3.749409                   4.805081   \n",
       "4998       68001.33124             5.465612                   7.130144   \n",
       "4999       65510.58180             5.007695                   6.792336   \n",
       "\n",
       "      Area Population        size  \n",
       "0         23086.80050  188.214212  \n",
       "1         40173.07217  160.042526  \n",
       "2         36882.15940  227.273544  \n",
       "3         34310.24283  164.816630  \n",
       "4         26354.10947  161.966659  \n",
       "...               ...         ...  \n",
       "4995      22837.36103  161.641403  \n",
       "4996      25616.11549  159.164596  \n",
       "4997      33266.14549  139.491785  \n",
       "4998      42625.62016  184.845371  \n",
       "4999      46501.28380  148.589423  \n",
       "\n",
       "[5000 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#define X_multi\n",
    "X_multi = data.drop(['Price'],axis=1)\n",
    "X_multi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#set up 2nd linear model\n",
    "LR_multi = LinearRegression()\n",
    "#train the model\n",
    "LR_multi.fit(X_multi,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1223968.89166086 1497306.3318863  1250884.31019437 ... 1020693.92390376\n",
      " 1260503.36914585 1302737.7915763 ]\n"
     ]
    }
   ],
   "source": [
    "#make prediction\n",
    "y_predict_multi = LR_multi.predict(X_multi)\n",
    "print(y_predict_multi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10219846512.17786 0.9180229195220739\n"
     ]
    }
   ],
   "source": [
    "mean_squared_error_multi = mean_squared_error(y,y_predict_multi)\n",
    "r2_score_multi = r2_score(y,y_predict_multi)\n",
    "print(mean_squared_error_multi,r2_score_multi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "108771672553.6264\n"
     ]
    }
   ],
   "source": [
    "print(mean_squared_error_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig7 = plt.figure(figsize=(8,5))\n",
    "plt.scatter(y,y_predict_multi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig8 = plt.figure(figsize=(8,5))\n",
    "plt.scatter(y,y_predict_1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[65000     5     5 30000   200]]\n"
     ]
    }
   ],
   "source": [
    "X_test = [65000,5,5,30000,200]\n",
    "X_test = np.array(X_test).reshape(1,-1)\n",
    "print(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[817052.19516298]\n"
     ]
    }
   ],
   "source": [
    "y_test_predict = LR_multi.predict(X_test)\n",
    "print(y_test_predict)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "线性回归房价实战summary：\n",
    "1、通过搭建线性回归模型，实现单因子的房屋价格预测；\n",
    "2、在单因子模型效果不好的情况下，通过考虑更多的因子，建立了多因子模型；\n",
    "3、多因子模型达到了更好的预测效果，r2分数为0.91；\n",
    "4、实现了预测结果的可视化，直观对比预测价格与实际价格的差异。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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